TCGA BRCA

library(clusterProfiler)
hallmark <- msigdbr::msigdbr(species = "Homo sapiens", category = "H") %>% 
  dplyr::select(gs_name, gene_symbol)

gs_names = hallmark$gs_name %>% unique()

hallmakrList = list()

# 리스트 초기화
hallmarkList <- list()

# 반복문을 사용하여 각 고유 gs_name에 대해 필터링 및 리스트 생성
for (i in seq_along(gs_names)) {
  hallmarkList[[gs_names[i]]] <- hallmark %>% 
    filter(gs_name == gs_names[i]) %>% 
    dplyr::select(gene_symbol) %>% 
    pull()
}

## Perform ssgsea 
library(corto)

## Input data : tpm (count.mtx is accepted as well) 
test = ssgsea(tpms,hallmarkList)

## Reshape it to plot 
test.df = test %>% t() %>% data.frame()
rownames(test.df) = colnames(tpms)

## p value of ssgsea 
pval = corto::z2p(test)
colnames(pval) = rownames(test.df)

# meta = colData(dds)
meta = TCGA_BRCA_tpmsMeta$meta
anno.col = meta[,"sample_type"] %>% as.data.frame()
rownames(anno.col) = rownames(meta)
colnames(anno.col) = "sample"
anno.col = anno.col %>% arrange(sample)

## Heatmap 
my.color=c(colorRampPalette(colors = c("#2874A6","white"))(70),
           colorRampPalette(colors = c("white","#D35400"))(70))
t(test.df[rownames(anno.col),]) %>% pheatmap::pheatmap(color = my.color, 
                                  cluster_rows = T,
                                  cluster_cols = F,
                                  main = "ssGSEA of HALLMARK pathways",
                                  show_rownames = T,
                                  show_colnames = F,
                                  annotation_col = anno.col,
                                  fontsize_row = 7) # Simple heatmap 

## Heatmap 
my.color=c(colorRampPalette(colors = c("#2874A6","white"))(70),
           colorRampPalette(colors = c("white","#D35400"))(70))
t(test.df[rownames(anno.col),]) %>% pheatmap::pheatmap(color = my.color, 
                                  cluster_rows = T,
                                  cluster_cols = T,
                                  main = "ssGSEA of HALLMARK pathways",
                                  show_rownames = T,
                                  show_colnames = F,
                                  annotation_col = anno.col,
                                  fontsize_row = 5) # Simple heatmap 

kegg <- msigdbr::msigdbr(species = "Homo sapiens", subcategory = "CP:KEGG") %>% 
  dplyr::select(gs_name, gene_symbol)

gs_names = kegg$gs_name %>% unique()

geneList = list()

# 리스트 초기화
geneList <- list()

# 반복문을 사용하여 각 고유 gs_name에 대해 필터링 및 리스트 생성
for (i in seq_along(gs_names)) {
  geneList[[gs_names[i]]] <- kegg %>% 
    filter(gs_name == gs_names[i]) %>% 
    dplyr::select(gene_symbol) %>% 
    pull()
}

## Perform ssgsea 
library(corto)

## Input data : tpm (count.mtx is accepted as well) 
test = ssgsea(tpms,geneList)

## Reshape it to plot 
test.df = test %>% t() %>% data.frame()
rownames(test.df) = colnames(tpms)

## p value of ssgsea 
pval = corto::z2p(test)
colnames(pval) = rownames(test.df)

## Heatmap 
my.color=c(colorRampPalette(colors = c("#2874A6","white"))(70),
           colorRampPalette(colors = c("white","#D35400"))(70))
t(test.df[rownames(anno.col),]) %>% pheatmap::pheatmap(color = my.color, 
                                  cluster_rows = T,
                                  cluster_cols = F,
                                  main = "ssGSEA of KEGG pathways",
                                  show_rownames = T,
                                  show_colnames = F,
                                  annotation_col = anno.col,
                                  fontsize_row = 5) # Simple heatmap 

## Heatmap 
my.color=c(colorRampPalette(colors = c("#2874A6","white"))(70),
           colorRampPalette(colors = c("white","#D35400"))(70))
t(test.df[rownames(anno.col),]) %>% pheatmap::pheatmap(color = my.color, 
                                  cluster_rows = T,
                                  cluster_cols = T,
                                  main = "ssGSEA of KEGG pathways",
                                  show_rownames = T,
                                  show_colnames = F,
                                  annotation_col = anno.col,
                                  fontsize_row = 5) # Simple heatmap